A digital sensor refers to a sensor with a microcontroller, a memory, and a certain intelligence. The sensor portion of the digital sensor may be an electrochemical sensor such as: a pH electrode; an ion selective electrode; or an oxygen sensor—in particular, a dissolved oxygen sensor. The sensor may be a conductivity sensor. The sensor may also be an optical sensor—especially, a turbidity sensor, or a sensor for optically determining the number of cells or cell structures.
Over time, sensors increasingly deviate from ideal behavior as a result of aging due to the influence of external conditions that burden the sensor, as well as from internal changes. This deviation from ideal behavior results in a shifting of the measurement chain characteristic curve. It is therefore common practice to carry out a correction from time to time to compensate for the deviation. This is quite common in electrochemical sensors such as pH electrodes, ion selective electrodes, oxygen sensors—in particular, dissolved oxygen sensors—and even in conductivity sensors. Such a correction, in which the display value of the sensor is aligned with the true value of the measurement, is called adjustment.
Digital sensors for process automation are usually calibrated and adjusted during production. In the following, this calibration and adjustment during production will be referred to as a “factory adjustment.” The adjustment data for this factory adjustment are stored permanently in a memory in the digital sensor and cannot be overwritten by subsequent calibrations and adjustments.
The users themselves perform calibrations and adjustments. In the following, this adjustment by the user shall be referred to as “user adjustment.” The adjustment data for this user adjustment are also stored in a memory in the digital sensor. This storage location is limited, and only a certain amount of adjustment data can be stored. This amount varies depending upon the type and manufacturer of the sensor. Commonly two to ten sets of adjustment data can be stored. Typically a FIFO storage sequence (First In, First Out) is used. When the memory is full, newer adjustment data can overwrite the older adjustment data.
The memory with the history of the adjustment data is available for the status evaluation of the sensor. Thus, a drift or atypical sensor behavior can be determined by comparing multiple stored adjustment data, and a statement can be made on the sensor status. Usually a status evaluation of the adjustment data in the memory relates to comparing the data from the last available adjustments to the data from the factory adjustment. Changes in the sensor since the beginning of its implementation (i.e., its first use by the user) can thus not be fully considered. This has a negative influence on the status evaluation of the sensor. Therefore, there is a need for improvements in this area of technology.